Breaking down barriers: exploring the impact of social capital on knowledge sharing and transfer in the workplace

The study addresses how organizations can revitalize internal knowledge flows disrupted by the COVID-19 pandemic by leveraging structured knowledge management processes (KMP) and employees’ social dynamics. Grounded in social exchange theory, the research examines whether KMP (acquisition, dissemination, application) fosters employees’ knowledge sharing and transfer, and how social capital (relational and structural) shapes KMP and, in turn, knowledge behaviors. The context emphasizes knowledge as a strategic asset for innovation, competitive advantage, and resilience. The paper seeks to clarify underexplored informal governance and motivational mechanisms behind knowledge sharing/transfer, especially in the information service sector, proposing that trust-based, reciprocal social exchange enhances employees’ alignment with KMP and catalyzes knowledge flows.

The literature integrates social exchange theory, knowledge management processes, and social capital. Social exchange theory (Blau, 1964) frames knowledge sharing as a reciprocal, relationship-building exchange in which KMP serves as an intermediary linking donors and recipients. Knowledge transfer is defined as directional transmission involving offering, assimilation, translation, and application of knowledge; knowledge sharing involves mutual exchange, codification, and use of platforms that reduce costs and risks. KMP’s core components—knowledge acquisition (KA), knowledge dissemination (KD), and knowledge application (KAP)—enable organizational innovation, performance, and competitive advantage beyond mere platform provision. Prior work notes tensions between organizational expectations to share and individuals’ incentives to withhold. Social capital is conceptualized along relational (trust, reciprocity, mutual respect) and structural (network configuration, density, connectivity) dimensions that facilitate cooperation and knowledge flows. Both dimensions are argued to reinforce KMP and knowledge behaviors, with hypotheses: H1 KMP positively impacts knowledge sharing; H2 KMP positively impacts knowledge transfer; H3a relational social capital positively impacts KMP; H3b structural social capital positively impacts KMP; H4a relational social capital positively impacts knowledge sharing; H4b structural social capital positively impacts knowledge sharing; H5a relational social capital positively impacts knowledge transfer; H5b structural social capital positively impacts knowledge transfer.

Design and sampling: A purposive sampling approach targeted R&D workers in the information service industry in mainland China, focusing on high-tech firms located in major hubs (e.g., Shanghai, Shenzhen, Guangzhou). Administrative personnel were excluded. Ethical approval was obtained from the Ethics Committee of Foshan University; informed consent was collected. An electronic questionnaire yielded 483 valid responses out of 490 (98.6% response rate). Participants were predominantly male (63.1%), held master’s degrees or above (61.4%), aged 30–40 (72.1%), with an average of 5.2 years’ experience. Measures: Five-point Likert scales (1 = strongly disagree, 5 = strongly agree) were used. Social capital (relational and structural) items adapted from Tsai et al. (2014), Lin and Huang (2010), Yilmaz and Hunt (2001), and Croteau and Raymond (2004). KMP (KA, KD, KAP) scales adapted from Shahzad et al. (2020) and Migdadi (2021). Knowledge sharing from Al-Emran et al. (2018) assessing motivation, opportunities, and behavior. Knowledge transfer adapted from Reagans and McEvily (2003). Analysis strategy: Structural Equation Modeling (SEM) was applied. Measurement model assessment included CFA, item loadings (>0.70), reliability (Cronbach’s alpha and composite reliability >0.70), and convergent validity (AVE >0.50). Discriminant validity followed Fornell–Larcker criteria. For structural analysis, PLS-SEM (SmartPLS 3.0) evaluated relationships; collinearity was checked (VIF < 3), and bootstrapping with 5000 subsamples provided inference. Model quality metrics included SRMR, NFI, Q2, and R2.

Measurement model showed satisfactory reliability and validity (all factor loadings > 0.70; Cronbach’s alpha and CR > 0.70; AVE > 0.50). Discriminant validity was supported (Fornell–Larcker). Hypotheses testing results (PLS-SEM): - H1: KMP → knowledge sharing, β = 0.634, p < 0.001 (supported) - H2: KMP → knowledge transfer, β = 0.587, p < 0.001 (supported) - H3a: Relational social capital → KMP, β = 0.464, p < 0.001 (supported) - H3b: Structural social capital → KMP, β = 0.525, p < 0.001 (supported) - H4a: Relational social capital → knowledge sharing, β = 0.532, p < 0.001 (supported) - H4b: Structural social capital → knowledge sharing, β = 0.214, p < 0.001 (supported) - H5a: Relational social capital → knowledge transfer, β = 0.324, p < 0.001 (supported) - H5b: Structural social capital → knowledge transfer, β = 0.413, p < 0.001 (supported) Collinearity was not a concern (all VIF < 3). Overall, both relational and structural social capital positively influenced KMP and, directly and indirectly, enhanced employees’ knowledge sharing and transfer behaviors.

Findings affirm that a structured KMP—spanning acquisition, dissemination, and application—promotes employees’ knowledge sharing and transfer by creating a formalized environment that streamlines information flows and supports decision-making and innovation. Social exchange mechanisms and organizational socialization further strengthen individuals’ inclination to share. Both structural and relational social capital bolster KMP and directly enhance knowledge behaviors: structural capital provides the network pathways for information flow, while relational capital improves the quality of exchanges via trust, norms, and reciprocity. Elevated social capital encourages participation in knowledge activities and deepens the assimilation and use of tacit and explicit knowledge, reinforcing a virtuous cycle of knowledge innovation. The results substantiate theoretical perspectives on bonding and bridging capital, highlighting the importance of trust, shared language, and cross-functional ties in sustaining effective knowledge governance.

This study contributes by empirically demonstrating that KMP significantly enhances knowledge sharing and transfer among employees and that both relational and structural social capital are key antecedents of KMP and knowledge behaviors. Using a large sample of R&D workers in China and SEM, it clarifies how social capital channels and relationship quality underpin effective knowledge governance. Practical implications include instituting comprehensive KMP, nurturing trust-based networks, breaking down organizational silos, and aligning incentives to foster continuous knowledge exchange. Future research should integrate broader theoretical lenses (e.g., embeddedness, absorptive capacity), examine the mediating role of social capital within knowledge governance, and conduct cross-country comparative studies to assess cultural and regional contingencies in knowledge behaviors.

The study centers on social interaction perspectives of KMP and does not integrate alternative frameworks such as embeddedness theory or absorptive capacity, which could enrich explanatory power. Social capital was treated as an antecedent; future work should test its mediating role in knowledge governance. The sample is confined to Chinese high-tech/information service contexts, limiting generalizability; cross-country comparisons are needed to explore cultural and regional effects on knowledge sharing and transfer.